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      Lamin A molecular compression and sliding as mechanisms behind nucleoskeleton elasticity

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          Abstract

          Lamin A is a nuclear intermediate filament protein critical for nuclear architecture and mechanics and mutated in a wide range of human diseases. Yet little is known about the molecular architecture of lamins and mechanisms of their assembly. Here we use SILAC cross-linking mass spectrometry to determine interactions within lamin dimers and between dimers in higher-order polymers. We find evidence for a compression mechanism where coiled coils in the lamin A rod can slide onto each other to contract rod length, likely driven by a wide range of electrostatic interactions with the flexible linkers between coiled coils. Similar interactions occur with unstructured regions flanking the rod domain during oligomeric assembly. Mutations linked to human disease block these interactions, suggesting that this spring-like contraction can explain in part the dynamic mechanical stretch and flexibility properties of the lamin polymer and other intermediate filament networks.

          Abstract

          Lamin A is critical for nuclear architecture but its structure and assembly are not fully understood. Here, the authors use quantitative cross-linking mass spectrometry to map intra- and intermolecular interactions within lamin homomers, providing insights into the molecular basis for lamin’s mechanical properties.

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          Protein structure homology modeling using SWISS-MODEL workspace.

          Homology modeling aims to build three-dimensional protein structure models using experimentally determined structures of related family members as templates. SWISS-MODEL workspace is an integrated Web-based modeling expert system. For a given target protein, a library of experimental protein structures is searched to identify suitable templates. On the basis of a sequence alignment between the target protein and the template structure, a three-dimensional model for the target protein is generated. Model quality assessment tools are used to estimate the reliability of the resulting models. Homology modeling is currently the most accurate computational method to generate reliable structural models and is routinely used in many biological applications. Typically, the computational effort for a modeling project is less than 2 h. However, this does not include the time required for visualization and interpretation of the model, which may vary depending on personal experience working with protein structures.
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            The RosettaDock server for local protein–protein docking

            The RosettaDock server (http://rosettadock.graylab.jhu.edu) identifies low-energy conformations of a protein–protein interaction near a given starting configuration by optimizing rigid-body orientation and side-chain conformations. The server requires two protein structures as inputs and a starting location for the search. RosettaDock generates 1000 independent structures, and the server returns pictures, coordinate files and detailed scoring information for the 10 top-scoring models. A plot of the total energy of each of the 1000 models created shows the presence or absence of an energetic binding funnel. RosettaDock has been validated on the docking benchmark set and through the Critical Assessment of PRedicted Interactions blind prediction challenge.
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              Serverification of Molecular Modeling Applications: the Rosetta Online Server that Includes Everyone (ROSIE)

              The Rosetta molecular modeling software package provides experimentally tested and rapidly evolving tools for the 3D structure prediction and high-resolution design of proteins, nucleic acids, and a growing number of non-natural polymers. Despite its free availability to academic users and improving documentation, use of Rosetta has largely remained confined to developers and their immediate collaborators due to the code's difficulty of use, the requirement for large computational resources, and the unavailability of servers for most of the Rosetta applications. Here, we present a unified web framework for Rosetta applications called ROSIE (Rosetta Online Server that Includes Everyone). ROSIE provides (a) a common user interface for Rosetta protocols, (b) a stable application programming interface for developers to add additional protocols, (c) a flexible back-end to allow leveraging of computer cluster resources shared by RosettaCommons member institutions, and (d) centralized administration by the RosettaCommons to ensure continuous maintenance. This paper describes the ROSIE server infrastructure, a step-by-step 'serverification' protocol for use by Rosetta developers, and the deployment of the first nine ROSIE applications by six separate developer teams: Docking, RNA de novo, ERRASER, Antibody, Sequence Tolerance, Supercharge, Beta peptide design, NCBB design, and VIP redesign. As illustrated by the number and diversity of these applications, ROSIE offers a general and speedy paradigm for serverification of Rosetta applications that incurs negligible cost to developers and lowers barriers to Rosetta use for the broader biological community. ROSIE is available at http://rosie.rosettacommons.org.
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                Author and article information

                Contributors
                juri.rappsilber@ed.ac.uk
                e.schirmer@ed.ac.uk
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                11 July 2019
                11 July 2019
                2019
                : 10
                : 3056
                Affiliations
                [1 ]ISNI 0000 0004 1936 7988, GRID grid.4305.2, Wellcome Centre for Cell Biology, , University of Edinburgh, ; Max Born Crescent, Edinburgh, EH9 3BF UK
                [2 ]ISNI 0000 0001 0462 7212, GRID grid.1006.7, Institute for Cell and Molecular Biosciences/NUPPA, The Medical School, , University of Newcastle, ; Framlington Place, Newcastle upon Tyne, NE2 4HH UK
                [3 ]ISNI 0000 0001 2292 8254, GRID grid.6734.6, Chair of Bioanalytics, Institute of Biotechnology, , Technische Universität Berlin, ; Berlin, 13355 Germany
                Author information
                http://orcid.org/0000-0002-0980-1723
                http://orcid.org/0000-0002-4376-8242
                http://orcid.org/0000-0001-5999-1310
                http://orcid.org/0000-0003-2635-1338
                Article
                11063
                10.1038/s41467-019-11063-6
                6624373
                31296869
                4c3b36f5-588e-4fe8-be8c-f9dd491e6514
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 19 September 2018
                : 20 June 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000848, University of Edinburgh;
                Funded by: University of Edinburgh Principal’s PhD Scholarship
                Funded by: Wellcome Centre for Cell Biology core grant 092076
                Funded by: Welcome Senior Research Fellowship 092509
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                cytoskeletal proteins,molecular modelling,electron microscopy,mass spectrometry,nucleoskeleton

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